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Athena: Automated Tuning of k-mer based Genomic Error Correction Algorithms using Language Models
The performance of most error-correction (EC) algorithms that operate on genomics reads is dependent on the proper choice of its configuration parameters, such as the value of k in k-mer based techniques. In this work, we target the problem of finding the best values of these configuration parameter...
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| Publicado no: | Sci Rep |
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| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Nature Publishing Group UK
2019
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6834855/ https://ncbi.nlm.nih.gov/pubmed/31695060 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41598-019-52196-4 |
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